GoogleGemma 2 9B Instruct on NVIDIA GeForce RTX 3080 10GB
Yes — RTX 3080 10GB runs Gemma 2 9B Instruct excellently at Q4_K_M — 45 tok/s. 10 GB VRAM with plenty of headroom.
Model Size
9.24B
Device VRAM
10 GB
Bandwidth
760 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 2 9B Instruct on NVIDIA GeForce RTX 3080 10GB at Q4_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q4_K_M | 45 tok/s | 135ms | ✓ Yes | Excellent | estimated |
Notes
Q4_K_M
Q4_K_M fits in 10GB. 760 GB/s makes 9B feel snappy.
About Gemma 2 9B Instruct
Gemma 2 9B Instruct (9.24B) is a chat, coding, reasoning, multi-purpose model. Google's 9B model with effective knowledge distillation. Competitive with Llama 3.1 8B on most benchmarks. Shorter max context (8K) is the main limitation vs Llama.
View all Gemma 2 9B Instruct hardware options →About NVIDIA GeForce RTX 3080 10GB
NVIDIA GeForce RTX 3080 10GB has 10 GB at 760 GB/s. Street price: $399.
See all models NVIDIA GeForce RTX 3080 10GB can run →Estimate method: Performance estimates based on model size and device bandwidth. Reference hardware source: github.com (2026-03-15)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.